Our long-term objective is to describe the molecular events that underlie colorectal cancer. Advances in technology permit the simultaneous measurements of thousands of different mRNA transcripts. There have also been notable advances in rapidly and efficiently scoring DNA abnormalities in mathematical approaches for organizing and exploring this information. Our plan is to harness all of these abilities in the service of a molecular understanding of tumor formation, progression, and metastasis. This should both enable us to discern new cancer pathway genes and to replace the current morphological classification of cancer with a more precise system based upon the molecular state of the abnormal cell. Our specific aims are: (i) Array Development: To develop and validate a colon cancer cDNA microarray. Using the Affymetrix U 95 Chip Set (60,000 full-length genes and ESTs), we will screen 120 microdissected tissue samples (90 abnormal, 30 normal) representing the full range of colorectal neoplasia. Approaches that are delineated and described in Project 3 will be used to select 4,000 to 6,000 features for a colon-oriented cDNA microarray. Features representing other known or suspected cancer pathway genes (see Project 1, and from the literature) will also be included in the colon-oriented cDNA microarray array. (ii) Gene Discovery: To identify expression changes in individual and groups of transcripts as colonic epithelium is transformed through aberrant crypts, adenomatous polyps, adenocarcinomas, and metastatic tissue. To target the associated genes for mutational analysis (in concert with Project 1 and Project 3) and assess their role in neoplasia. Genes will be identified that are abnormally expressed in neoplastic epithelium and in concert with Project 1 are shown to have an associated genetic or epigenetic abnormality. These candidate oncogenes or tumor suppressor genes will be characterized by: (i) in situ hybridization, (ii) promoter and coding sequence analysis, (iii) clonogenic and tumorigenic assays, (iv) cell cycle analysis, (v) animal models, and (vi) mechanistic studies. (iii) Outcome prediction: To develop a molecular taxonomy of colorectal cancer by relating concerted patterns of gene expression to clinical and genetic information. In concert with Projects 1 and 3, we propose to develop an approach to tumor classification and clinical outcome prediction that is grounded in a comprehensive evaluation of transcript abundance, DNA markers, and clinico-pathological status. By relating patterns of gene expression and gene mutation to fundamental indicators of disease status, we may be more able to precisely predict the clinical behavior of a tumor.